******************************************************************
** Article: How parties can shape their competence reputations: **
**			issue attention, position, and performance			**
** Journal: European Journal of Political Research				**
** Date:	September 2024	 									**
** Authors:	Stiers & Dassonneville								**
******************************************************************


***Load dataset
use "Data_experiment.dta", clear
	
set scheme bw
grstyle init
grstyle set plain, nogrid noextend
	

*** Main analyses ***

***Figure 4: Marginal means competence reputations
//Estimate model
conjoint Choice_ownership Choice_attention Choice_ideology Choice_issuestatus Choice_partysize Choice_partystatus , estimate(mm) id(RespondentID)
//Save results in matrix
matrix results = e(results) 
//Figure 4
coefplot (matrix(results[,1])) , ci((5 6)) keep(*:) xline(0.5, lpattern(-) lcolor(black)) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues= "One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"   Worsened= "Worsened"  Improved= "Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" In_opposition= "In opposition"  Inc_no_minister= "Incumbent no minister" Inc_with_minister= "Incumbent with minister") eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}" "{bf:Status party}", asheadings) scale(0.7) xtitle({bf:Marginal means})


***Figure 5: Marginal means competence reputations for subgroups
//Estimate model
conjoint Choice_ownership Choice_attention Choice_ideology Choice_issuestatus Choice_partysize , estimate(mm) id(RespondentID) subgroup(Choice_partystatus)
//Save results in matrix
matrix results_0=e(results_In_opposition) 
matrix results_1=e(results_Inc_no_minister)
matrix results_2=e(results_Inc_with_minister)
//Figure 5
coefplot  matrix(results_0[,1]), xline(0.4759, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Opposition") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7 0.4759 "0.48") name(Figure_5_1,replace)

coefplot  matrix(results_1[,1]), xline(0.4713, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Incumbent" "no minister") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7 0.4713 "0.47") name(Figure_5_2,replace)

coefplot  matrix(results_2[,1]), xline(0.5486, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Incumbent" "with minister") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7 0.5491 "0.55") name(Figure_5_3,replace)

graph combine Figure_5_1 Figure_5_2 Figure_5_3, r(1) xsize(5)


***Figure 6: Self-reported reasons for the choice of issue owner
//Preserve experimental dataset for use below
preserve
//Load data set 
use "Data_open_question.dta" , clear
//Input data to make nicer figure
input Factor Amount
1 388	//Attention
2 307	//Party status
3 270	//Party position
4 196	//Party size
5 182	//Issue status
6 155	//Beliefs
7 227	//Feeling (106) + other (121)
end
//Figure 6
twoway bar Amount Factor, xlabel(1 "Issue attention" 2 "Status party" 3 "Ideological position" 4 "Party size" 5 "Status issue" 6 "Shared position" 7 "Other" , angle(45)) xtitle("Mentioned reason") ytitle("Number of mentions") ylabel(0(100)400)
//Restore dataset experiment for further replication
restore


*** Analyses appendices ***

***Appendix O
*Figure O.1: Replication of Figure 4 for issues owned by the left
//Estimate model
conjoint Choice_ownership Choice_attention Choice_ideology Choice_issuestatus Choice_partysize Choice_partystatus if core_left==1 , estimate(mm) id(RespondentID)
matrix results = e(results) 
//Figure O.1
coefplot (matrix(results[,1])) , ci((5 6)) keep(*:) xline(0.5, lpattern(-) lcolor(black)) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues= "One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"   Worsened= "Worsened"  Improved= "Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" In_opposition= "In opposition"  Inc_no_minister= "Incumbent no minister" Inc_with_minister= "Incumbent with minister") eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}" "{bf:Status party}", asheadings) scale(0.7) xtitle({bf:Marginal means})

*Figure O.2: Replication of Figure 5 for issues owned by the left
//Estimate model
conjoint Choice_ownership Choice_attention Choice_ideology Choice_issuestatus Choice_partysize if core_left==1 , estimate(mm) id(RespondentID) subgroup(Choice_partystatus)
matrix results_0=e(results_In_opposition) 
matrix results_1=e(results_Inc_no_minister)
matrix results_2=e(results_Inc_with_minister)
//Figure O.2
coefplot  matrix(results_0[,1]), xline(0.4759, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Opposition") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7 0.4759 "0.48") name(Figure_O2_1,replace)

coefplot  matrix(results_1[,1]), xline(0.4713, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Incumbent" "no minister") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7 0.4713 "0.47") name(Figure_O2_2,replace)

coefplot  matrix(results_2[,1]), xline(0.5486, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Incumbent" "with minister") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7 0.5491 "0.55") name(Figure_O2_3,replace)

graph combine Figure_O2_1 Figure_O2_2 Figure_O2_3 , r(1) xsize(5)

*Figure O.3: Replication of Figure 4 for issues owned by the right
//Estimate model
conjoint Choice_ownership Choice_attention Choice_ideology Choice_issuestatus Choice_partysize Choice_partystatus if core_right==1 , estimate(mm) id(RespondentID)
matrix results = e(results) 
//Figure O.3
coefplot (matrix(results[,1])) , ci((5 6)) keep(*:) xline(0.5, lpattern(-) lcolor(black)) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues= "One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"   Worsened= "Worsened"  Improved= "Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" In_opposition= "In opposition"  Inc_no_minister= "Incumbent no minister" Inc_with_minister= "Incumbent with minister") eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}" "{bf:Status party}", asheadings) scale(0.7) xtitle({bf:Marginal means})

*Figure O.4: Replication of Figure 4 for issues owned by the right
//Estimate model
conjoint Choice_ownership Choice_attention Choice_ideology Choice_issuestatus Choice_partysize if core_right==1 , estimate(mm) id(RespondentID) subgroup(Choice_partystatus)
matrix results_0=e(results_In_opposition) 
matrix results_1=e(results_Inc_no_minister)
matrix results_2=e(results_Inc_with_minister)
//Figure O.4
coefplot  matrix(results_0[,1]), xline(0.4759, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Opposition") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7 0.4759 "0.48") name(Figure_O4_1,replace)

coefplot  matrix(results_1[,1]), xline(0.4713, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Incumbent" "no minister") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7 0.4713 "0.47") name(Figure_O4_2,replace)

coefplot  matrix(results_2[,1]), xline(0.5486, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Incumbent" "with minister") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7 0.5491 "0.55") name(Figure_O4_3,replace)

graph combine Figure_O4_1 Figure_O4_2 Figure_O4_3 , r(1) xsize(5)


***Appendix P
*Figure P.1: Replication of Figure 4 using a continuous dependent variable
//Estimate model
conjoint Choice_competence Choice_attention Choice_ideology Choice_issuestatus Choice_partysize Choice_partystatus , estimate(mm) id(RespondentID)
matrix results = e(results) 
//Figure P.1
coefplot (matrix(results[,1])) , ci((5 6)) keep(*:) xline(5.776094, lpattern(-) lcolor(black)) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues= "One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"   Worsened= "Worsened"  Improved= "Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" In_opposition= "In opposition"  Inc_no_minister= "Incumbent no minister" Inc_with_minister= "Incumbent with minister") eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}" "{bf:Status party}", asheadings) scale(0.7) xtitle({bf:Marginal means})

*Figure P.2: Replication of Figure 5 using a continuous dependent variable
//Estimate model
conjoint Choice_competence Choice_attention Choice_ideology Choice_issuestatus Choice_partysize , estimate(mm) id(RespondentID) subgroup(Choice_partystatus)
matrix results_0=e(results_In_opposition) 
matrix results_1=e(results_Inc_no_minister)
matrix results_2=e(results_Inc_with_minister)
//Figure P.2
coefplot  matrix(results_0[,1]), xline(5.7674305, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Opposition") scale(0.7) xtitle(Marginal means) xlabel(4.5(0.5)6.5) name(Figure_P2_1,replace)

coefplot  matrix(results_1[,1]), xline(5.5625597, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Incumbent" "no minister") scale(0.7) xtitle(Marginal means) xlabel(4.5(0.5)6.5) name(Figure_P2_2,replace)

coefplot  matrix(results_2[,1]), xline(5.9822616, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Incumbent" "with minister") scale(0.7) xtitle(Marginal means) xlabel(4.5(0.5)6.5) name(Figure_P2_3,replace)

graph combine Figure_P2_1 Figure_P2_2 Figure_P2_3 , r(1) xsize(5)


***Appendix Q
*Figure Q.1: Replication of Figure 4 using the vote choice as dependent variable
//Estimate model
conjoint Choice_election Choice_attention Choice_ideology Choice_issuestatus Choice_partysize Choice_partystatus , estimate(mm) id(RespondentID)
matrix results = e(results) 
//Figure Q.1
coefplot (matrix(results[,1])) , ci((5 6)) keep(*:) xline(0.5, lpattern(-) lcolor(black)) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues= "One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"   Worsened= "Worsened"  Improved= "Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" In_opposition= "In opposition"  Inc_no_minister= "Incumbent no minister" Inc_with_minister= "Incumbent with minister") eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}" "{bf:Status party}", asheadings) scale(0.7) xtitle({bf:Marginal means})

*Figure Q.2: Replication of Figure 5 using the vote choice as dependent variable
//Estimate model
conjoint Choice_election Choice_attention Choice_ideology Choice_issuestatus Choice_partysize , estimate(mm) id(RespondentID) subgroup(Choice_partystatus)
matrix results_0=e(results_In_opposition) 
matrix results_1=e(results_Inc_no_minister)
matrix results_2=e(results_Inc_with_minister)
//Figure Q.2
coefplot  matrix(results_0[,1]), xline(0.48415407, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Opposition") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7) name(Figure_Q2_1,replace)

coefplot  matrix(results_1[,1]), xline(0.47086915, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Incumbent" "no minister") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7) name(Figure_Q2_2,replace)

coefplot  matrix(results_2[,1]), xline(0.54146341, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Incumbent" "with minister") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7) name(Figure_Q2_3,replace)

graph combine Figure_Q2_1 Figure_Q2_2 Figure_Q2_3 , r(1) xsize(5)


***Appendix R
*Figure R.1: Replication of Figure 4 using only the first conjoint task
//Estimate model
conjoint Choice_ownership Choice_attention Choice_ideology Choice_issuestatus Choice_partysize Choice_partystatus if Party==1|Party==2 , estimate(mm) id(RespondentID)
matrix results = e(results) 
//Figure R.1
coefplot (matrix(results[,1])) , ci((5 6)) keep(*:) xline(0.5, lpattern(-) lcolor(black)) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues= "One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"   Worsened= "Worsened"  Improved= "Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" In_opposition= "In opposition"  Inc_no_minister= "Incumbent no minister" Inc_with_minister= "Incumbent with minister") eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}" "{bf:Status party}", asheadings) scale(0.7) xtitle({bf:Marginal means})

*Figure R.2: Replication of Figure 5 using only the first conjoint task
//Estimate model
conjoint Choice_ownership Choice_attention Choice_ideology Choice_issuestatus Choice_partysize if Party==1|Party==2 , estimate(mm) id(RespondentID) subgroup(Choice_partystatus)
matrix results_0=e(results_In_opposition) 
matrix results_1=e(results_Inc_no_minister)
matrix results_2=e(results_Inc_with_minister)
//Figure R.2
coefplot  matrix(results_0[,1]), xline(0.47540984, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Opposition") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7) name(Figure_R2_1,replace)

coefplot  matrix(results_1[,1]), xline(0.48747592, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Incumbent" "no minister") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7) name(Figure_R2_2,replace)

coefplot  matrix(results_2[,1]), xline(0.53422222, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Incumbent" "with minister") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7) name(Figure_R2_3,replace)

graph combine Figure_R2_1 Figure_R2_2 Figure_R2_3 , r(1) xsize(5)


***Appendix S
*Figure S.1: Individual-level traits and choice of most important issue
//preserve dataset for further replication below
preserve
//Estimate model
mlogit Most_important_issue i.sex age i.edu Leftright_self_alt
//Generate figure by issue
//Economy
margins, dydx(sex age edu Leftright_self_alt) predict(out(1))
marginsplot, recast(scatter) recastci(rspike) plot1opts(msymbol(o)) yline(0,lpattern(shortdash)) title("Economy",size(vsmall)) ytitle("AME",size(vsmall)) ylabel(,labsize(vsmall)) xlabel(1 "Female" 2 "Age" 3 `""Higher" "Educated""' 4 "Ideology",labsize(vsmall)) xtitle("Effect of...",size(vsmall)) name(Figure_S1_1,replace) nodraw
//Immigration
margins, dydx(sex age edu Leftright_self_alt) predict(out(2))
marginsplot, recast(scatter) recastci(rspike) plot1opts(msymbol(o)) yline(0,lpattern(shortdash)) title("Immigration",size(vsmall)) ytitle("AME",size(vsmall)) ylabel(,labsize(vsmall)) xlabel(1 "Female" 2 "Age" 3 `""Higher" "Educated""' 4 "Ideology",labsize(vsmall)) xtitle("Effect of...",size(vsmall)) name(Figure_S1_2,replace) nodraw
//Crime
margins, dydx(sex age edu Leftright_self_alt) predict(out(3))
marginsplot, recast(scatter) recastci(rspike) plot1opts(msymbol(o)) yline(0,lpattern(shortdash)) title("Crime",size(vsmall)) ytitle("AME",size(vsmall)) ylabel(,labsize(vsmall)) xlabel(1 "Female" 2 "Age" 3 `""Higher" "Educated""' 4 "Ideology",labsize(vsmall)) xtitle("Effect of...",size(vsmall)) name(Figure_S1_3,replace) nodraw
//Taxes
margins, dydx(sex age edu Leftright_self_alt) predict(out(5))
marginsplot, recast(scatter) recastci(rspike) plot1opts(msymbol(o)) yline(0,lpattern(shortdash)) title("Taxes",size(vsmall)) ytitle("AME",size(vsmall)) ylabel(,labsize(vsmall)) xlabel(1 "Female" 2 "Age" 3 `""Higher" "Educated""' 4 "Ideology",labsize(vsmall)) xtitle("Effect of...",size(vsmall)) name(Figure_S1_4,replace) nodraw
//Social security
margins, dydx(sex age edu Leftright_self_alt) predict(out(6))
marginsplot, recast(scatter) recastci(rspike) plot1opts(msymbol(o)) yline(0,lpattern(shortdash)) title("Social security",size(vsmall)) ytitle("AME",size(vsmall)) ylabel(,labsize(vsmall)) xlabel(1 "Female" 2 "Age" 3 `""Higher" "Educated""' 4 "Ideology",labsize(vsmall)) xtitle("Effect of...",size(vsmall)) name(Figure_S1_5,replace) nodraw
//Healthcare
margins, dydx(sex age edu Leftright_self_alt) predict(out(7))
marginsplot, recast(scatter) recastci(rspike) plot1opts(msymbol(o)) yline(0,lpattern(shortdash)) title("Health care",size(vsmall)) ytitle("AME",size(vsmall)) ylabel(,labsize(vsmall)) xlabel(1 "Female" 2 "Age" 3 `""Higher" "Educated""' 4 "Ideology",labsize(vsmall)) xtitle("Effect of...",size(vsmall)) name(Figure_S1_6,replace) nodraw
//Environment
margins, dydx(sex age edu Leftright_self_alt) predict(out(8))
marginsplot, recast(scatter) recastci(rspike) plot1opts(msymbol(o)) yline(0,lpattern(shortdash)) title("Environment",size(vsmall)) ytitle("AME",size(vsmall)) ylabel(,labsize(vsmall)) xlabel(1 "Female" 2 "Age" 3 `""Higher" "Educated""' 4 "Ideology",labsize(vsmall)) xtitle("Effect of...",size(vsmall)) name(Figure_S1_7,replace) nodraw
//Defence
margins, dydx(sex age edu Leftright_self_alt) predict(out(9))
marginsplot, recast(scatter) recastci(rspike) plot1opts(msymbol(o)) yline(0,lpattern(shortdash)) title("Defence",size(vsmall)) ytitle("AME",size(vsmall)) ylabel(,labsize(vsmall)) xlabel(1 "Female" 2 "Age" 3 `""Higher" "Educated""' 4 "Ideology",labsize(vsmall)) xtitle("Effect of...",size(vsmall)) name(Figure_S1_8,replace) nodraw
//Poverty
margins, dydx(sex age edu Leftright_self_alt) predict(out(10))
marginsplot, recast(scatter) recastci(rspike) plot1opts(msymbol(o)) yline(0,lpattern(shortdash)) title("Poverty",size(vsmall)) ytitle("AME",size(vsmall)) ylabel(,labsize(vsmall)) xlabel(1 "Female" 2 "Age" 3 `""Higher" "Educated""' 4 "Ideology",labsize(vsmall)) xtitle("Effect of...",size(vsmall)) name(Figure_S1_9,replace) nodraw
//Norms and values
margins, dydx(sex age edu Leftright_self_alt) predict(out(11))
marginsplot, recast(scatter) recastci(rspike) plot1opts(msymbol(o)) yline(0,lpattern(shortdash)) title("Norms and values",size(vsmall)) ytitle("AME",size(vsmall)) ylabel(,labsize(vsmall)) xlabel(1 "Female" 2 "Age" 3 `""Higher" "Educated""' 4 "Ideology",labsize(vsmall)) xtitle("Effect of...",size(vsmall)) name(Figure_S1_10,replace) nodraw
//Energy
margins, dydx(sex age edu Leftright_self_alt) predict(out(12))
marginsplot, recast(scatter) recastci(rspike) plot1opts(msymbol(o)) yline(0,lpattern(shortdash)) title("Energy",size(vsmall)) ytitle("AME",size(vsmall)) ylabel(,labsize(vsmall)) xlabel(1 "Female" 2 "Age" 3 `""Higher" "Educated""' 4 "Ideology",labsize(vsmall)) xtitle("Effect of...",size(vsmall)) name(Figure_S1_11,replace) nodraw
//Education
margins, dydx(sex age edu Leftright_self_alt) predict(out(13))
marginsplot, recast(scatter) recastci(rspike) plot1opts(msymbol(o)) yline(0,lpattern(shortdash)) title("Education",size(vsmall)) ytitle("AME",size(vsmall)) ylabel(,labsize(vsmall)) xlabel(1 "Female" 2 "Age" 3 `""Higher" "Educated""' 4 "Ideology",labsize(vsmall)) xtitle("Effect of...",size(vsmall)) name(Figure_S1_12,replace) nodraw
//Employment
margins, dydx(sex age edu Leftright_self_alt) predict(out(14))
marginsplot, recast(scatter) recastci(rspike) plot1opts(msymbol(o)) yline(0,lpattern(shortdash)) title("Employment",size(vsmall)) ytitle("AME",size(vsmall)) ylabel(,labsize(vsmall)) xlabel(1 "Female" 2 "Age" 3 `""Higher" "Educated""' 4 "Ideology",labsize(vsmall)) xtitle("Effect of...",size(vsmall)) name(Figure_S1_13,replace) nodraw
//Housing
margins, dydx(sex age edu Leftright_self_alt) predict(out(15))
marginsplot, recast(scatter) recastci(rspike) plot1opts(msymbol(o)) yline(0,lpattern(shortdash)) title("Housing",size(vsmall)) ytitle("AME",size(vsmall)) ylabel(,labsize(vsmall)) xlabel(1 "Female" 2 "Age" 3 `""Higher" "Educated""' 4 "Ideology",labsize(vsmall)) xtitle("Effect of...",size(vsmall)) name(Figure_S1_14,replace) nodraw
//EU
margins, dydx(sex age edu Leftright_self_alt) predict(out(16))
marginsplot, recast(scatter) recastci(rspike) plot1opts(msymbol(o)) yline(0,lpattern(shortdash)) title("EU",size(vsmall)) ytitle("AME",size(vsmall)) ylabel(,labsize(vsmall)) xlabel(1 "Female" 2 "Age" 3 `""Higher" "Educated""' 4 "Ideology",labsize(vsmall)) xtitle("Effect of...",size(vsmall)) name(Figure_S1_15,replace) nodraw
//Figure S.1
graph combine Figure_S1_1 Figure_S1_2 Figure_S1_3 Figure_S1_4 Figure_S1_5 Figure_S1_6 Figure_S1_7 Figure_S1_8 Figure_S1_9 Figure_S1_10 Figure_S1_11 Figure_S1_12 Figure_S1_13 Figure_S1_14 Figure_S1_15 , ycommon
restore

*Figure S.2: Subgroup analyses sex
//Estimate model
conjoint Choice_ownership Choice_attention Choice_ideology Choice_issuestatus Choice_partysize , estimate(mm) id(RespondentID) subgroup(sex)
matrix results_0=e(results__0) 
matrix results_1=e(results__1)
//Figure S.2
coefplot matrix(results_0[,1]), xline(0.5, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Male respondents") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7) name(Figure_S2_1,replace)

coefplot  matrix(results_1[,1]), xline(0.5, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Female respondents") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7) name(Figure_S2_2,replace)

graph combine Figure_S2_1 Figure_S2_2 , r(1) 

*Figure S.3: Subgroup analysis age
//Estimate model
conjoint Choice_ownership Choice_attention Choice_ideology Choice_issuestatus Choice_partysize , estimate(mm) id(RespondentID) subgroup(age_dich)
matrix results_0=e(results__0) 
matrix results_1=e(results__1)
//Figure S.3
coefplot matrix(results_0[,1]), xline(0.5, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Youngest respondents") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7) name(Figure_S3_1,replace)

coefplot  matrix(results_1[,1]), xline(0.5, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Oldest respondents") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7) name(Figure_S3_2,replace)

graph combine Figure_S3_1 Figure_S3_2 , r(1) 

*Figure S.4: Subgroup analysis educational level
//Estimate model
conjoint Choice_ownership Choice_attention Choice_ideology Choice_issuestatus Choice_partysize , estimate(mm) id(RespondentID) subgroup(edu)
matrix results_0=e(results__0) 
matrix results_1=e(results__1)
//Figure S.4
coefplot matrix(results_0[,1]), xline(0.5, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Lower educated respondents") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7) name(Figure_S4_1,replace)

coefplot  matrix(results_1[,1]), xline(0.5, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Higher educated respondents") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7) name(Figure_S4_2,replace)

graph combine Figure_S4_1 Figure_S4_2 , r(1) 

*Figure S.5: Subgroup analysis ideological position
//Estimate model
conjoint Choice_ownership Choice_attention Choice_ideology Choice_issuestatus Choice_partysize , estimate(mm) id(RespondentID) subgroup(Leftright_self)
matrix results_1=e(results__1)
matrix results_2=e(results__2)
matrix results_3=e(results__3)
matrix results_4=e(results__4)
matrix results_5=e(results__5)
//Figure S.5
coefplot matrix(results_1[,1]), xline(0.5, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Extreme left respondents") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7) name(Figure_S5_1,replace)

coefplot  matrix(results_2[,1]), xline(0.5, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Left respondents") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7) name(Figure_S5_2,replace)

coefplot  matrix(results_3[,1]), xline(0.5, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Centrist respondents") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7) name(Figure_S5_3,replace)

coefplot  matrix(results_4[,1]), xline(0.5, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Right respondents") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7) name(Figure_S5_4,replace)

coefplot  matrix(results_5[,1]), xline(0.5, lpattern(-) lcolor(black)) || , ci((5 6)) keep(*:) msymbol(0) coeflabels( Not_much_attention= "Not much attention"  One_of_the_issues="One of the issues"  Main_issue= "Main issue"  Centrist= "Centrist"  Left_right= "Left/right"  Extreme_left_right= "Extreme left/right"  Worsened= "Worsened"  Improved="Improved"  _5_= "5%"  _15_= "15%"  _25_= "25%" ) eqlabels( "{bf:Attention for issue}" "{bf:Ideological position}" "{bf:Status issue}" "{bf:Party size}", asheadings) subtitle("Extreme right respondents") scale(0.7) xtitle(Marginal means) xlabel(0.3(0.1)0.7) name(Figure_S5_5,replace)

graph combine Figure_S5_1 Figure_S5_2 Figure_S5_3 Figure_S5_4 Figure_S5_5
